Evaluation of LANDSAT-4 TM and MSS ground geometry performance without ground control

Techniques and software developed to characterize the Washington, D.C. scene were improved and are being systematically applied to an Imperial Valley, CA scene. Digital elevation files are being acquired. One hundred seventy-two tiepoints were located in the Imperial Valley scene. They were digitized from USGS maps to determine their lat-long coordinates. A least squares fit is currently being performed between line-sample image data and the lat-long positions of the tiepoints. Thematic mapper scanner sweeps were determined for the Imperial Valley P-data. VICAR jobs are currently under way to analyze sample-direction offsets between sweeps in the data, as well as band to band registration offsets. Tiepoint location is about to begin in the Harrisburg, PA scene

LANDSAT Digital Data Base Preparation for the Pennsylvania Defoliation Application Pilot Test

A LANDSAT digital mosaic data base for the State of Pennsylvania was prepared for use in the development of an automated system to annually estimate the extent and severity of Gypsy Moth defoliation of hardward forests. The techniques for detecting the defoliation and development of a geographic information system (GIS) to assess damage is being developed jointly by NASA/Goddard Space Flight Center and Pennsylvania State University using the JPL prepared mosaic base. The JPL processing involved the use of ground control points from the Master Data Processor for planimetric control, resampling of the LANDSAT data to 57 x 57 meter pixels, realignment to north, and reprojection to the Universal Transverse Mercator (UTM) projection in UTM zones 17 and 18. The completed mosaic for each UTM zone was subdivided into 1 degree of latitude by 2 degrees of longitude quadrangles for easy data handling. Consideration is given to the issues of mapping standards, sensor and spacecraft platform characteristics, and their implication to geographic information systems operation. Methods for obtaining measures of accuracy for LANDSAT mosaics are reviewed

Computational aspects of remapping digital imagery

One of the advantages of automated cartography is that map data stored in the digital computer can be plotted or displayed at any scale or projection by recomputing the coordinates of the data. This is especially easy in the case of vector (graphics) data but in the case of digital image (raster) data, remapping is a more difficult operation. Examples of the remapping of digital imagery would include rectification of a LANDSAT MSS to an orthographic or Mercator projection, warping of one image to register with another, or rotation, scale, or aspect changes of a digital image. Use of general purpose computers and array processors for this task will be covered. Data processing error will be discussed for each modelling/warping approach

Digital computer synthesis of admittance matrices of N+1 nodes

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Extension Professionals\u27 Perspectives on Supporting Feedstock Production for Biofuels: Concerns, Challenges, and Opportunities

The development of successful bioenergy programs will depend on informed and prepared Extension professionals who are willing and equipped to provide technical support. A survey of Extension professionals in the Pacific Northwest revealed barriers to program development, including limits on time and knowledge and concerns about economic returns for biofuel crops. Without the promise of market opportunities, Extension professionals may be unwilling to devote requisite resources to bioenergy programs. However, government policies and mandates make the rise of biofuels highly likely. Extension professionals should look to the future and consider blending bioenergy education into existing programs

Growing Green Energy: A Review of Extension\u27s Role in the Development of Advanced Biofuels

The development of advanced biofuels is expanding the possibilities for purpose-grown energy crops. Growers, producers, and other stakeholders will need a reliable source of information to assist with decision-making regarding renewable fuel supply chains. This review examines Extension\u27s role in the innovation of advanced biofuels by documenting and summarizing Extension work in existing biomass-derived energy programs. This review highlights strategies used by Extension programs that help make renewable energy innovations successful

Fast Locality-Sensitive Hashing Frameworks for Approximate Near Neighbor Search

The Indyk-Motwani Locality-Sensitive Hashing (LSH) framework (STOC 1998) is a general technique for constructing a data structure to answer approximate near neighbor queries by using a distribution $\mathcal{H}$ over locality-sensitive hash functions that partition space. For a collection of $n$ points, after preprocessing, the query time is dominated by $O(n^{\rho} \log n)$ evaluations of hash functions from $\mathcal{H}$ and $O(n^{\rho})$ hash table lookups and distance computations where $\rho \in (0,1)$ is determined by the locality-sensitivity properties of $\mathcal{H}$. It follows from a recent result by Dahlgaard et al. (FOCS 2017) that the number of locality-sensitive hash functions can be reduced to $O(\log^2 n)$, leaving the query time to be dominated by $O(n^{\rho})$ distance computations and $O(n^{\rho} \log n)$ additional word-RAM operations. We state this result as a general framework and provide a simpler analysis showing that the number of lookups and distance computations closely match the Indyk-Motwani framework, making it a viable replacement in practice. Using ideas from another locality-sensitive hashing framework by Andoni and Indyk (SODA 2006) we are able to reduce the number of additional word-RAM operations to $O(n^\rho)$.Comment: 15 pages, 3 figure